• Structural Engineering and Mechanics
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• v.3 no.3
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• pp.273-287
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• 1995

Stochastic response of systems to random excitation can be estimated by direct integration methods in the time domain such as the stochastic central difference method (SCDM). In this paper, the SCDM is applied to compute the variance and covariance in response of linear and nonlinear structures subjected to random excitation. The accuracy of the SCDM is assessed using two-DOF systems with both deterministic and random material properties excited by white noise. For the former case, closed-form solutions can be obtained. Numerical results also are presented for a simply supported geometrically nonlinear beam. The stiffness of this beam is modeled as a random field, and the beam is idealized by the stochastic finite element method. A perturbation technique is applied to formulate the equations of motion of the system, and the dynamic structural response statistics are obtained in a time domain analysis. The effect of variations in structural parameters and the numerical stability of the SCDM also are examined.

• Korean System Dynamics Review
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• v.12 no.1
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• pp.115-130
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• 2011

This study shows the operational availability(Ao) analysis of the supply chain with maintenance functions using the system dynamics simulation. The simulation uses 60 equipments which are serial systems composed by 4 major components. And every entities are connected each other by causal loops. So whole simulation executed like one organic system. Specially we consider 2 constraints, one is the number of spare parts and the other is maintenance capacity level. 2 constraints have 11 levels each so the simulation has 121(11*11) scenarios which scenario has 30 different random number seed. The simulation executed total 3,630(11*11*30) times. We analysis average Ao of total equipments by 121 scenarios and additionally the regression of the average Ao and 2 constraints. As the result, we can get the more accurate values by the system dynamics simulation than the regression to analysis complex system like the supply chain with maintenance functions.

• Structural Engineering and Mechanics
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• v.57 no.1
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• pp.21-43
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• 2016

A conditional probability based approach known as Particle Filter Method (PFM) is a powerful tool for system parameter identification. In this paper, PFM has been applied to identify the vehicle parameters based on response statistics of the bridge. The flexibility of vehicle model has been considered in the formulation of bridge-vehicle interaction dynamics. The random unevenness of bridge has been idealized as non homogeneous random process in space. The simulated response has been contaminated with artificial noise to reflect the field condition. The performance of the identification system has been examined for various measurement location, vehicle velocity, bridge surface roughness factor, noise level and assumption of prior probability density. Identified vehicle parameters are found reasonably accurate and reconstructed interactive force time history with identified parameters closely matches with the simulated results. The study also reveals that crude assumption of prior probability density function does not end up with an incorrect estimate of parameters except requiring longer time for the iterative process to converge.

• Wind and Structures
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• v.10 no.2
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• pp.153-176
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• 2007

The Proper Orthogonal Decomposition (POD) is a statistical method particularly suitable and versatile for dealing with many problems concerning wind engineering and several other scientific and humanist fields. POD represents a random process as a linear combination of deterministic functions, the POD modes, modulated by uncorrelated random coefficients, the principal components. It owes its popularity to the property that only few terms of the series are usually needed to capture the most energetic coherent structures of the process, and a link often exists between each dominant mode and the main mechanisms of the phenomenon. For this reason, POD modes are normally used to identify low-dimensional subspaces appropriate for the construction of reduced models. This paper provides a state-of-the-art and some prospects on POD, with special regard to its framework and applications in wind engineering. A wide bibliography is also reported.

• Earthquakes and Structures
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• v.8 no.4
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• pp.915-934
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• 2015

Within the context of Structural Health Monitoring (SHM), it is often the case that structural systems are described by uncertainty, both with respect to their parameters and the characteristics of the input loads. For the purposes of system identification, efficient modeling procedures are of the essence for a fast and reliable computation of structural response while taking these uncertainties into account. In this work, a reduced order metamodeling framework is introduced for the challenging case of nonlinear structural systems subjected to earthquake excitation. The introduced metamodeling method is based on Nonlinear AutoRegressive models with eXogenous input (NARX), able to describe nonlinear dynamics, which are moreover characterized by random parameters utilized for the description of the uncertainty propagation. These random parameters, which include characteristics of the input excitation, are expanded onto a suitably defined finite-dimensional Polynomial Chaos (PC) basis and thus the resulting representation is fully described through a small number of deterministic coefficients of projection. The effectiveness of the proposed PC-NARX method is illustrated through its implementation on the metamodeling of a five-storey shear frame model paradigm for response in the region of plasticity, i.e., outside the commonly addressed linear elastic region. The added contribution of the introduced scheme is the ability of the proposed methodology to incorporate uncertainty into the simulation. The results demonstrate the efficiency of the proposed methodology for accurate prediction and simulation of the numerical model dynamics with a vast reduction of the required computational toll.

• Proceedings of the Korean Magnestics Society Conference
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• 2010.06a
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• pp.15-16
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• 2010

• Bulletin of the Korean Mathematical Society
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• v.60 no.4
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• pp.1131-1139
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• 2023

In this paper, we introduce the concept of ω-expansive of random map on compact metric spaces 𝓟. Also we introduce the definitions of positively, negatively shadowing property and shadowing property for two-sided RDS. Then we show that if 𝜑 is ω-expansive and has the shadowing property for ω, then 𝜑 is topologically stable for ω.

• Transactions of the Korean Society of Mechanical Engineers B
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• v.26 no.2
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• pp.194-200
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• 2002

A method for simulating flow of extremely low Reynolds number in a vortex-in-cell (VIC) was studied. The viscous diffusion was represented by the random walk method. The validity of this method was proven by applying it to the flows passing over a fence placed vertically at an extremely low Reynolds number. The effects of parameters of the VIC method on the random walk method, such as the number of point vortices, the mesh density and the time increment, were investigated by numerical analysis using a one-dimensional diffusion equation. Changes in the relative error of vorticity depending on those parameters were clarified.

• Bulletin of the Korean Chemical Society
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• v.28 no.10
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• pp.1697-1704
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• 2007

We present results for transport properties of diatomic fluids by isothermal-isobaric (NpT) equilibrium molecular dynamics (EMD) simulations using Green-Kubo and Einstein formulas. As the molecular elongation of diatomic molecules increases from the spherical monatomic molecule, the diffusion coefficient increases, indicating that longish shape molecules diffuse more than spherical molecules, and the rotational diffusion coefficients are almost the same in the statistical error since random rotation decreases. The calculated translational viscosity decreases with the molecular elongation of diatomic molecule within statistical error bar, while the rotational viscosity increases. The total thermal conductivity decreases as the molecular elongation increases. This result of thermal conductivity for diatomic molecules by EMD simulations is again inconsistent with the earlier results of those by non-equilibrium molecular dynamics (NEMD) simulations even though the missing terms related to rotational degree of freedom into the Green-Kubo and Einstein formulas with regard to the calculation of thermal conductivity for molecular fluids are included.

• 한국전산유체공학회:학술대회논문집
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• 2008.03a
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• pp.204-207
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• 2008

Stochastic molecular dynamics simulation is a variation of standard molecular dynamics simulation that basically omits water molecules. The omission of water molecules, occupying a majority of space, enables flow simulation at microscale. This study reports our stochastic molecular dynamics simulation of particles diffusing in rectangular microchannels. We interestingly found that diffusion patterns in channels with a very small aspect ratio differ by dimensions. We will also discuss the future direction of our research toward a more realistic simulation of micromixing.